Enterprise AI Infrastructure

One Gateway. Any AI. Anywhere.

One secure, centrally governed gateway to every AI model your organisation uses: cloud, enterprise, and privately hosted. Applications integrate once. You decide who uses which model, through which provider, at what cost.

Govern · Private AI · Vendor independence

Request a demo Explore products

OpenAI-compatible API Self-hosted Budgets in RM

Policy · Finance / ERP Assistant

Enforced

Allowed providers

Private AI Azure OpenAI Public cloud AI

Monthly budget

RM 1,284 / 2,000

Request limit

100 req / min

Peak today: 62

10:42 · ERP Assistant → Private AI200 OK
10:42 · Finance Analytics → Azure OpenAI200 OK
10:41 · ERP Assistant → Public cloud AIBlocked by policy

The problem

AI adoption is fragmenting your organisation.

A typical enterprise now uses several AI platforms. When every application connects to every vendor directly, cost, risk, and complexity multiply.

Vendor fragmentation

Every AI provider has its own API, authentication, pricing, and limits. Applications get tightly coupled to one vendor, and switching means redevelopment.

No cost visibility

AI spend is scattered across departments, applications, API keys, and cloud accounts. Management cannot see who is consuming what.

Data governance risk

Customer data, financials, internal documents, and source code can end up in public AI services without anyone approving it.

Vendor dependency

Direct integrations inherit one vendor’s pricing, availability, model lifecycle, rate limits, and commercial terms.

Duplicated operations

IT maintains authentication, logging, usage tracking, security, and monitoring separately for every AI integration.

Private AI is hard

Regulated organisations want models inside their own infrastructure, with the same developer experience and governance as public AI.

How it works

Applications integrate once. The gateway handles the rest.

Your applications point their existing OpenAI SDK at NexianStack. The gateway authenticates, applies policy, and routes each request to an approved model, wherever it runs.

Client applications

Web & mobile apps · Developer applications · Internal tools · AI agents · ERP / CRM · Third-party integrations

↓ HTTPS · OpenAI-compatible API · API key / SSO

NexianStack AI Gateway · Control plane

Manage · Govern · Secure · Observe

Organisations, departments & projects
RBAC & SSO
API keys & access control
Data classification & policies
Budgets & cost control (RM)
Usage analytics & dashboards
Audit logs & compliance
Model & provider hub

↓ Policies · rate limits · model mapping

Routing engine · Data plane

Model routingLoad balancingFailoverRate limitsToken & cost trackingCaching

↓ Only to approved providers

Cloud AI

Public cloud AI providers

OpenAI · Anthropic · Google Gemini · Groq

Enterprise cloud AI

Managed AI in your cloud tenancy

Azure OpenAI · AWS Bedrock · Google Vertex AI

Self-hosted AI

Models on your own infrastructure

vLLM · Ollama · llama.cpp · Custom models

Product modules

Everything you need to run AI as a governed service.

Six modules give IT one place to publish models, manage providers, set policy, and watch usage, without touching application code.

AI Gateway

The unified, OpenAI-compatible interface your applications use. One integration, many providers, less vendor dependency.

Model Hub

A catalogue of approved models published as business-friendly profiles such as General, Fast, Reasoning, Vision, Speech, and Private AI.

Provider Hub

Cloud, enterprise cloud, and private AI providers managed in one place. Credentials and configuration stay central, never in application code.

Provider & model configuration

Decide which model or provider each application, department, project, or user can reach, based on cost, performance, workload, and location.

AI governance

Policies for allowed models and providers, request limits, budgets, permissions, private-only applications, and public-provider restrictions.

AI observability

Requests, tokens, cost, latency, errors, and provider health, broken down by application and department.

Governance

Policy that follows your organisation chart.

Structure AI governance the way your business is structured. Every department, project, and application can have its own models, providers, budgets, request limits, and security policies.

Organisation
Department
Project
Application
User

Example policy

Finance application

Allowed: Private AI · Azure OpenAI
Not allowed: Public cloud AI providers
Monthly budget: RM 2,000
Request limit: 100 requests / minute

Use cases

Where the gateway pays for itself.

From consolidating scattered AI spend to running models inside your own data centre.

Enterprise AI consolidation

Departments already using several AI providers move behind one gateway, so management sees users, applications, models, usage, and cost.

Private AI gateway

Run a model inside your own data centre. Applications keep a standard AI API while sensitive data never leaves your environment.

Provider-specific access

Finance runs on private AI, customer support on Azure OpenAI, and developer tools on an approved public provider. Each application is held to its own list.

Provider failover

When a provider is unavailable, requests move to another approved provider under failover rules you have configured and validated, with no application change.

AI cost optimisation

Send routine workloads to lower-cost models and reserve the most capable models for the tasks that need them.

Shared AI platform

ERP assistants, customer support, document processing, knowledge assistants, analytics, and AI agents all share one governed AI layer.

Supported AI workloads

Text & conversational AIVision & image understandingImage generationSpeech-to-textText-to-speechEmbeddingsAI agents & applications

Private deployment

Your infrastructure. Your models. Your data.

The complete gateway runs inside your environment, built for banking, government, data centres, and other security-sensitive organisations.

Runs entirely inside your infrastructure
Private networking and local data processing
Optional internet isolation / air-gapped install
Local AI model support
High-availability deployment
Enterprise RBAC, SSO, and audit

Enterprises

Multiple AI initiatives that need central governance and cost control.

Financial services

Banks, insurers, and fintechs with strict control over sensitive data.

Government & public sector

Private deployment, controlled data processing, and auditability.

Data centres & operators

Private compute already in place, ready to serve AI locally.

Healthcare & regulated

Stronger data governance and on-premise deployment.

Software & SaaS

AI embedded across many products on one internal AI layer.

NexianStack AI Platform

The foundation for every AI service you build next.

The gateway is the common access and governance layer beneath AI agents, knowledge and RAG, and private AI infrastructure.

AI Business Automation

Get started

Take control of how AI is used across your organisation.

Tell us which AI providers your teams use today and where your data must stay. We'll show you the gateway live, with your models and policies.

Request a demo Talk to us